Characterizing the Severity and Risk of Drought in the Poudre River, Colorado

Salas, José D.; Fu, C.; Cancelliere, Antonino; Dustin, Dony; Bode, Dennis; Pineda, Andy; Vincent, Esther

doi:10.1061/(asce)0733-9496(2005)131:5(383)

Cited by 127 publications

(100 citation statements)

References 20 publications

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“…Some recent works include, for example, Shiau [17] who constructed a joint drought duration and severity distribution using bivariate copulas in southern Taiwan; Zhang [18] employed a copula function to analyze drought risk, indicating a high risk in central and north-western Yunnan Province; and Tosunoglu and Can [19] used a two-dimensional copula function to analyze meteorological droughts in Turkey. Similar analyses can be found in [20][21][22][23].…”

Section: Introductionsupporting

confidence: 82%

An Entropy-Based Investigation into Bivariate Drought Analysis in China

Zuo

Hou

Jia

2017

Water

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Abstract:Because of the high correlation between random variables of drought duration and severity, their joint distribution is difficult to obtain by traditional mathematical methods. However, the copula method has proved to be a useful tool for analyzing the frequency of drought duration and severity. Most studies have used different marginal distribution functions to fit the drought duration and severity distributions. This requires a great deal of contrast analysis, and sometimes two or more distributions fit the data well. Based on entropy theory, however, a unified probability distribution function is derived which reduces complex contrast analysis and improves the filtering distribution function. Based on monthly precipitation data at 162 stations in China for 1961-2015, the monthly standardized precipitation index was calculated and used to extract drought duration and severity. Then the entropy distribution was used to fit the distributions of drought duration and severity, and to establish the correspondence between them. The probabilities of the interval and return periods were then determined using the copula method. An analysis of the discrepancy between the conventional and entropy-based methods indicated that the entropy distribution showed a better fit than conventional methods for drought duration distribution, although no obvious difference was found in drought severity distribution. The entropy-based results were more consistent with the empirical data, whereas conventional methods showed apparent deviation in some drought types. Hence, the entropy-based method is proposed as an alternative method of deriving the marginal distributions of drought duration and severity, and for analyzing the interval probability and return period in China.

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Section: Introductionsupporting

confidence: 82%

An Entropy-Based Investigation into Bivariate Drought Analysis in China

Zuo

Hou

Jia

2017

Water

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“…A familiar approach to describing the relationships between drought characteristics is to use the multivariate joint distribution of these characteristics. Most such studies have focused on the relationship between drought duration and severity for meteorological and hydrological droughts separately (Shiau and Shen 2001, Kim et al 2003, Salas et al 2005, Mishra et al 2009, Serinaldi et al 2009, Cancelliere and Salas 2010, Song and Singh 2010a, 2010b. For example, Shiau and Shen (2001) formulated a methodology for frequency and risk analysis of hydrological droughts using streamflow, and obtained a theoretical derivation of the recurrence interval of hydrological droughts above a certain severity.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic analysis of hydrological drought characteristics using meteorological drought

Wong

Lanen

Torfs

2013

Hydrological Sciences Journal

109

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Droughts are an inevitable consequence of climate variability and are pervasive across many regions. Their effects can vary on an extensive scale, depending on the type of drought and people's vulnerability. Crucial characteristics of both hydrological (groundwater, streamflow) and meteorological (precipitation) droughts are related to their durations and severities, and these characteristics are typically correlated. While many studies have addressed the dependencies between these characteristics for either the meteorological or hydrological drought, the cross-dependence between meteorological and hydrological drought characteristics is barely investigated. The development of meteorological drought characteristics to hydrological drought characteristics is often hard to model and their connection is not definitively established. In order to better understand and explain this relationship, this study seeks to apply statistical tools and models. Drought characteristics data from areas in Europe with different climates are analysed. Two approaches of identifying related meteorological and hydrological drought are explored and compared. Classical linear correlation techniques do not provide promising results, indicating that any statistic of a hydrological drought is not a straightforward function of a preceding meteorological drought. Subsequently, the application of the concept of copulas to explore this dependence between meteorological and hydrological drought characteristics is investigated. The more comprehensive approach of copulas shows that the meteorological drought contains probability information of the successive hydrological drought.Key words hydrological drought; meteorological drought; cross-dependence; copula; correlation; bivariate distribution; forecasting Analyse probabiliste des caractéristiques de la sécheresse hydrologique utilisant la sécheresse météorologique Résumé Les sécheresses sont une conséquence inévitable de la variabilité du climat et sont omniprésentes dans de nombreuses régions. Leurs effets peuvent énormément varier, en fonction du type de la sécheresse et de la vulnérabilité des populations. Les caractéristiques essentielles des sécheresses hydrologiques (eaux souterraines, débits) et météorologiques (précipitations) sont liées à leur durée et à leur sévérité, et ces caractéristiques sont généralement corrélées. Alors que de nombreuses études ont porté sur les dépendances entre ces caractéristiques soit pour les sécheresses météorologiques soit pour les sécheresses hydrologiques, la dépendance croisée entre les caractéristiques des sécheresses météorologiques et hydrologiques a à peine été abordée. Le passage des caractéris-tiques des sécheresses météorologiques à celles des sécheresses hydrologiques est souvent difficile à modéliser et leur relation n'est pas définitivement établie. Afin de mieux comprendre et expliquer cette relation, cette étude vise à appliquer des outils statistiques et des modèles. Des données des caractéristiques de sécheresses provenant de régi...

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“…Joint probability distribution function (Bonaccorso et al, 2003;Kim et al, 2003;Salas et al, 2005;Mirakbari et al, 2010). 또한, Gonzalez and Valdés(2003)는 수자원 시스템이 실패할 위험 정도를 해 석하는 데 있어 이변량 가뭄재현기간을 이용하였으며, 그 결과 이변량 가뭄빈도해석의 필요성을 재 증명한 바 있다.…”

Section: Copulaunclassified

“…따라서 최근에는 다양한 가뭄 특성인자 간의 관계 를 복합적으로 결합시켜 일관성이 있는 결과를 제시할 수 있는 가뭄해석방법의 필요성이 제기되고 있다. 특히 가뭄 은 지속기간과 심도를 주요 특성변수로 갖는 이변량 수문 사상이므로, 이 두 가지 변량의 발생분포 특성을 결합하 여 통계학적으로 유의한 결합분포함수의 확률을 추정하는 연구가 활발히 이루어지고 있다 (Shiau and Shen, 2001;Bonaccorso et al, 2003;Gonzalez and Valdés, 2003;Salas et al, 2005;Kim et al, 2006;Mirakbari et al, 2010).…”

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Drought Risk Analysis Using Stochastic Rainfall Generation Model and Copula Functions

유지영¹,

신지예²,

김동균³

et al. 2013

Journal of Korea Water Resources Association

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This study performed the bivariate drought frequency analysis for duration and severity of drought, using copula functions which allow considering the correlation structure of joint features of drought. We suggested the confidence intervals of duration-severity-frequency (DSF) curves for the given drought duration using stochastic scheme of monthly rainfall generation for 57 sites in Korea. This study also investigated drought risk via illustrating the largest drought events on record over 50 and 100 consecutive years. It appears that drought risks are much higher in some parts of the Nakdong River basin, southern and east coastal areas. However, such analyses are not always reliable, especially when the frequency analysis is performed based on the data observed over relatively short period of time. To quantify the uncertainty of drought frequency curves, the droughts were filtered by different durations. The 5%, 25%, 50%, 75%, and 95% confidence intervals of the drought severity for a given duration were estimated based on the simulated rainfall time series. Finally, it is shown that the growing uncertainties is revealed in the estimation of the joint probability using the two marginal distributions since the correlation coefficient of two variables is relatively low.

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Characterizing the Severity and Risk of Drought in the Poudre River, Colorado

Cited by 127 publications

References 20 publications

An Entropy-Based Investigation into Bivariate Drought Analysis in China

An Entropy-Based Investigation into Bivariate Drought Analysis in China

Probabilistic analysis of hydrological drought characteristics using meteorological drought

Drought Risk Analysis Using Stochastic Rainfall Generation Model and Copula Functions

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